Database Modernization for FinTechs

Vineet Singh, Pallavi Khopkar

While we’ve witnessed significant innovation across various parts of the application stack, such as front ends and middle-tier business logic, the pace of innovation at the database layer has not been as rapid. Relational databases remain the workhorse for many applications in financial services. In this blog, we’ll discuss how we can apply modernization techniques to the database tier.

Database demands for FinTechs


Let’s remind ourselves of the demands financial services firms place on their database engines.

  • Performance is crucial for systems like online banking, payment systems, and trade reconciliation systems, which may require thousands or tens of thousands of transactions per second.
  • Moreover, these technologies must be easy to use and apply for a broad community of developers and administrators.
  • Transactional integrity is vital, ensuring that transactions are accurately processed and recorded. As the world becomes more complex and demands evolve, flexibility in database engines is essential to support various applications, including web and mobile apps.
  • Finally, data durability is paramount, ensuring that data is retained securely without loss, meeting both customer and regulatory obligations.


Pain points in scaling traditional database implementations

Relational databases excel in maintaining consistency and transactional integrity, yet they also present certain drawbacks. Although capable of scaling to manage high transaction volumes, the underlying hardware and software stack frequently introduce complexity and vulnerabilities, accompanied by high costs.


SQL, despite its popularity and ease of use, lacks some modern language features and extensibility, limiting its flexibility. Relational databases also struggle with complex data relationships, where specialized databases like graph databases might offer better solutions.


Although relational databases provide durability and high availability, achieving these attributes often necessitates integration with modern storage solutions, thereby compounding the complexity and cost of the overall system.


Despite the advancements made in relational databases over the past few decades, there are still challenges, including maintenance costs and limitations in scalability and flexibility.


This underscores the need for rethinking database design and embracing innovative solutions like Amazon Aurora.

Modern AWS databases

Amazon Aurora revolutionizes database architecture by combining the speed and accessibility of commercial databases with the cost-effectiveness of open-source solutions. It appeals to financial institutions aiming to upgrade their database infrastructure without sacrificing performance or facing high costs, thanks to its unique storage and compute layers and compatibility with MySQL and PostgreSQL.

Amazon Aurora’s scale-out distributed framework is a game-changer, distributing storage volumes across multiple nodes spanning three availability zones, with each data segment replicated six times for enhanced resilience. This innovative setup ensures uninterrupted availability and durability, surpassing traditional database platforms’ complexities and costs, thanks to AWS’s streamlined management.

Furthermore, data is organized into protection groups, comprising 10-gigabyte blocks that dynamically expand as the database scales. Aurora autonomously adjusts provisioned space as required, eliminating the necessity for manual intervention in storage management.

Amazon’s DynamoDB
, a high-speed NoSQL database, scales seamlessly across AWS regions, boasting millisecond latency and automatic global replication via DynamoDB Global Tables. This frees up organizations’ IT and engineering resources from maintenance tasks, allowing them to focus on strategic business initiatives while AWS manages upkeep through pay-as-you-go services like Amazon Aurora.


Modern Design Practices


Move up the stack into value-added services

Move scarce IT and engineering talent towards strategic tasks aligned with business challenges, rather than operating and managing databases.

With Aurora’s pay-as-you-go model, AWS handles maintenance, freeing resources for innovation. Aurora and DynamoDB are architected on top of the Amazon regions and availability zones, providing automatic failover without requiring additional work. You can survive power and networking failures without resorting to asynchronous replication models. 


Make developers more productive by allowing them to choose the best database for the job


Traditionally, relational databases were a one-size-fits-all solution, but with options like Amazon Neptune for relationship-focused data, developers can optimize performance and complexity. AWS offers a range of database engines to cater to diverse use cases, such as Aurora for transactional systems and Redshift for analytics. By embracing this approach, businesses can avoid the impracticality of maintaining multiple technologies, as AWS handles maintenance and allows flexible, pay-as-you-go usage. This enables developers to leverage the best technology for every aspect of their applications, fostering innovation and efficiency.


Harness the power of API

Traditionally, teams would directly query the database, leading to complications during schema changes or upgrades. By implementing modern communication tools like APIs, teams can consume data without being tightly coupled to the database schema. This approach offers greater flexibility in database selection and schema modifications, enhancing development speed and enabling seamless separation of applications behind the scenes. Additionally, APIs streamline security measures and reduce the computational load on databases by centralizing connections and providing a controlled interface.

Comprinno is an AWS Advanced Consulting Partner and holds multiple AWS competencies like Migration, Security and Resilience.


We have helped numerous FinTechs in their migration and modernization journey in AWS.


Please reach out to us for more information and further insights.

About Author(s)

Vineet Singh is a Principal Solution Architect with a wealth of expertise in designing and implementing cutting-edge AWS solutions. Vineet plays a pivotal role in driving innovation and excellence in Comprinno’s cloud-based endeavors.

Pallavi Khopkar is a seasoned IT professional with over 14 years of experience in multiple domains and technologies. She currently heads the Center of Excellence initiative at Comprinno and is responsible for skill development, fostering collaboration among diverse teams, and ensuring the implementation of best practices to achieve excellence in the organization’s core areas of expertise.

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